It’s no secret that over the last year, companies have adopted and deployed big data architectures and analytics like never before. They’ve caught the big data bug and they’re using the insights gleaned from that data to anticipate, plan and react to situations in real-time. If your organization is doing this, then you’ve likely seen great results, but have you ever stopped to think about how secure your data and, in turn, your decisions are?
Decisions, changes and new technologies, like data analytics, are being implemented so quickly that legacy processes simply can’t keep up. The gap between new and legacy systems is often just wide enough for a security risk to slip through. Once these risks penetrate the gap, they’re moving at the speed of light themselves, diving into data and jumping back out before businesses even know what hit them. You don’t have to look far to see this happening – from recent and high-profile data breaches to stolen financial information, we’ve seen it all.
Herein lies our dilemma. How can we take full advantage of the volume, velocity and variety of data available today while ensuring the data remains secure?
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